Reliable multicast as a Bayesian coalition game for a non-stationary environment in vehicular ad hoc networks: a learning automata-based approach. (2015)

• Record Type: Journal Article
• Authors: Kumar, Neeraj; Lin, Chun-Cheng
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 19:Number 3/4(2015)
• Page Start: 168
• Page End: 182
• Publication Date: 2015
• Subjects: vehicular ad hoc networks -- VANETs -- learning automata -- coalition game -- Bayesian networks -- reliable multicasting -- multicast reliability -- conditional probability; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

Vehicular ad hoc networks (VANETs) are offering lot of services for the benefits of community of users. But, due to the dynamic nature of VANETs, it is a challenging task to perform reliable multicast. To address this issue, this paper proposes a new approach called reliable multicasting in non-stationary environment as a Bayesian coalition game using learning automata (RMBCG-LA) for VANETs. A new metric, probabilistic reliability index (PRI) is computed by each player. A coalition among the players of the game is formed using Bayesian network with a threshold in each coalition is based upon the conditional probability. For each action performed by the automaton, its action is rewarded or penalised by the non-stationary environment in which it is operates. The performance of the proposed scheme is evaluated in comparison with the well-known existing schemes. The results obtained show that our proposed scheme is better than the other schemes of its category.